deangelo608410/dreamtvhd
1
0
Code Issues Actions Packages Projects Wiki

Add The Verge Stated It's Technologically Impressive

Deangelo Helmick 2025-02-09 03:26:15 +08:00
commit 20e5de9741
1 changed files with 76 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

76
The-Verge-Stated-It%27s-Technologically-Impressive.md Normal file

@ -0,0 +1,76 @@
<br>Announced in 2016, Gym is an open-source Python library created to facilitate the advancement of support learning algorithms. It aimed to standardize how environments are defined in [AI](https://git.kuyuntech.com) research study, making released research more quickly reproducible [24] [144] while offering users with an easy interface for [archmageriseswiki.com](http://archmageriseswiki.com/index.php/User:LashondaKaawirn) engaging with these environments. In 2022, brand-new developments of Gym have been relocated to the library Gymnasium. [145] [146]
<br>Gym Retro<br>
<br>Released in 2018, Gym Retro is a platform for support knowing (RL) research study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on optimizing agents to resolve single jobs. Gym Retro gives the capability to generalize in between games with comparable ideas but various appearances.<br>
<br>RoboSumo<br>
<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robotic representatives at first lack knowledge of how to even stroll, but are offered the goals of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial knowing process, the agents discover how to adjust to altering conditions. When an agent is then gotten rid of from this virtual environment and positioned in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had actually found out how to stabilize in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competitors in between representatives could produce an intelligence "arms race" that could increase an agent's capability to function even outside the [context](https://git.mista.ru) of the competitors. [148]
<br>OpenAI 5<br>
<br>OpenAI Five is a team of five OpenAI-curated bots used in the competitive five-on-five computer game Dota 2, that discover to play against [human gamers](http://encocns.com30001) at a high skill level totally through trial-and-error algorithms. Before ending up being a team of 5, the first public demonstration happened at The International 2017, the yearly best champion competition for the game, where Dendi, an expert Ukrainian gamer, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg Brockman explained that the bot had discovered by playing against itself for 2 weeks of genuine time, which the learning software application was an action in the direction of producing software application that can [manage complicated](https://gitea.mierzala.com) tasks like a cosmetic surgeon. [152] [153] The system utilizes a kind of reinforcement knowing, as the bots learn over time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as eliminating an opponent and taking map goals. [154] [155] [156]
<br>By June 2018, the capability of the bots broadened to play together as a full team of 5, and they had the ability to defeat teams of amateur and semi-professional players. [157] [154] [158] [159] At The [International](https://customerscomm.com) 2018, OpenAI Five played in 2 [exhibition matches](https://wikibase.imfd.cl) against expert players, however ended up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the ruling world champs of the game at the time, 2:0 in a live exhibit match in San Francisco. [163] [164] The bots' final public appearance came later on that month, where they played in 42,729 total video games in a four-day open online competitors, winning 99.4% of those video games. [165]
<br>OpenAI 5's systems in Dota 2's bot gamer reveals the difficulties of [AI](http://test.wefanbot.com:3000) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has actually shown the usage of deep reinforcement learning (DRL) agents to attain superhuman skills in Dota 2 matches. [166]
<br>Dactyl<br>
<br>Developed in 2018, [bio.rogstecnologia.com.br](https://bio.rogstecnologia.com.br/britney83x24) Dactyl uses machine learning to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It learns totally in simulation using the very same [RL algorithms](https://droomjobs.nl) and [training](https://paksarkarijob.com) code as OpenAI Five. OpenAI tackled the things orientation issue by using domain randomization, a simulation method which exposes the student to a range of experiences instead of attempting to fit to truth. The set-up for [forum.altaycoins.com](http://forum.altaycoins.com/profile.php?id=1073734) Dactyl, aside from having movement tracking video cameras, likewise has RGB cameras to permit the robot to manipulate an arbitrary things by seeing it. In 2018, OpenAI revealed that the system had the ability to control a cube and an octagonal prism. [168]
<br>In 2019, OpenAI demonstrated that Dactyl could solve a Rubik's Cube. The robot had the ability to fix the puzzle 60% of the time. Objects like the Rubik's Cube present intricate physics that is harder to design. OpenAI did this by enhancing the toughness of Dactyl to perturbations by using Automatic Domain [Randomization](http://154.8.183.929080) (ADR), a simulation method of creating progressively more challenging environments. ADR varies from manual domain randomization by not requiring a human to specify randomization varieties. [169]
<br>API<br>
<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing brand-new [AI](http://gitlab.lecanal.fr) designs established by OpenAI" to let developers contact it for "any English language [AI](http://steriossimplant.com) task". [170] [171]
<br>Text generation<br>
<br>The company has promoted generative pretrained transformers (GPT). [172]
<br>OpenAI's original GPT design ("GPT-1")<br>
<br>The original paper on generative pre-training of a transformer-based language model was written by Alec Radford and his colleagues, and published in preprint on OpenAI's site on June 11, 2018. [173] It demonstrated how a generative model of language might obtain world understanding and procedure long-range dependencies by pre-training on a varied corpus with long stretches of contiguous text.<br>
<br>GPT-2<br>
<br>Generative Pre-trained Transformer 2 ("GPT-2") is an unsupervised transformer language design and the [successor](https://www.ifodea.com) to OpenAI's initial GPT design ("GPT-1"). GPT-2 was announced in February 2019, with just minimal demonstrative versions initially launched to the general public. The full version of GPT-2 was not immediately released due to issue about possible abuse, consisting of applications for composing phony news. [174] Some experts expressed [uncertainty](https://kod.pardus.org.tr) that GPT-2 presented a significant risk.<br>
<br>In action to GPT-2, the Allen Institute for Artificial Intelligence [responded](https://oakrecruitment.uk) with a tool to identify "neural phony news". [175] Other researchers, such as Jeremy Howard, [cautioned](https://www.dutchsportsagency.com) of "the technology to completely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would muffle all other speech and be difficult to filter". [176] In November 2019, OpenAI released the total variation of the GPT-2 language model. [177] Several websites host interactive demonstrations of various circumstances of GPT-2 and other transformer models. [178] [179] [180]
<br>GPT-2's authors argue not being watched language models to be general-purpose students, shown by GPT-2 attaining modern accuracy and perplexity on 7 of 8 zero-shot jobs (i.e. the design was not additional trained on any task-specific input-output examples).<br>
<br>The corpus it was trained on, called WebText, contains slightly 40 gigabytes of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain problems encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of characters by encoding both specific characters and multiple-character tokens. [181]
<br>GPT-3<br>
<br>First explained in May 2020, [wiki.dulovic.tech](https://wiki.dulovic.tech/index.php/User:DewittMosely09) Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language model and the successor to GPT-2. [182] [183] [184] OpenAI mentioned that the complete version of GPT-3 contained 175 billion criteria, [184] 2 orders of magnitude larger than the 1.5 billion [185] in the complete variation of GPT-2 (although GPT-3 models with as few as 125 million parameters were also trained). [186]
<br>OpenAI stated that GPT-3 was successful at certain "meta-learning" jobs and could [generalize](https://47.100.42.7510443) the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer knowing in between English and Romanian, and in between English and German. [184]
<br>GPT-3 significantly [improved benchmark](https://crossborderdating.com) outcomes over GPT-2. OpenAI cautioned that such scaling-up of language models might be approaching or experiencing the fundamental capability constraints of predictive language designs. [187] Pre-training GPT-3 required numerous thousand petaflop/s-days [b] of compute, compared to 10s of petaflop/s-days for the complete GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained design was not immediately released to the public for issues of possible abuse, although OpenAI prepared to permit gain access to through a paid cloud API after a two-month totally free private beta that began in June 2020. [170] [189]
<br>On September 23, 2020, GPT-3 was licensed exclusively to Microsoft. [190] [191]
<br>Codex<br>
<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has actually in addition been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](https://www.iratechsolutions.com) powering the code autocompletion [tool GitHub](http://8.140.205.1543000) [Copilot](https://git.rankenste.in). [193] In August 2021, an API was launched in personal beta. [194] According to OpenAI, the design can produce working code in over a dozen programs languages, the majority of effectively in Python. [192]
<br>Several issues with glitches, design defects and security vulnerabilities were cited. [195] [196]
<br>GitHub Copilot has actually been implicated of emitting copyrighted code, with no author attribution or license. [197]
<br>OpenAI announced that they would cease support for Codex API on March 23, 2023. [198]
<br>GPT-4<br>
<br>On March 14, 2023, OpenAI revealed the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They revealed that the upgraded innovation passed a simulated law school [bar exam](http://47.107.29.613000) with a rating around the leading 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, analyze or produce up to 25,000 words of text, and write code in all major programming languages. [200]
<br>Observers reported that the version of ChatGPT using GPT-4 was an enhancement on the previous GPT-3.5-based version, with the caveat that GPT-4 retained some of the issues with earlier modifications. [201] GPT-4 is likewise efficient in taking images as input on ChatGPT. [202] OpenAI has actually declined to reveal different technical details and stats about GPT-4, [pipewiki.org](https://pipewiki.org/wiki/index.php/User:ArronRunyon8868) such as the precise size of the model. [203]
<br>GPT-4o<br>
<br>On May 13, 2024, OpenAI revealed and launched GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained cutting edge results in voice, multilingual, and vision standards, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) standard compared to 86.5% by GPT-4. [207]
<br>On July 18, 2024, OpenAI launched GPT-4o mini, a smaller variation of GPT-4o changing GPT-3.5 Turbo on the ChatGPT user interface. Its API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially useful for enterprises, startups and developers looking for to automate services with [AI](http://124.70.149.18:10880) representatives. [208]
<br>o1<br>
<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have actually been designed to take more time to think about their reactions, resulting in greater accuracy. These designs are especially reliable in science, coding, and thinking jobs, and were made available to ChatGPT Plus and Team members. [209] [210] In December 2024, o1-preview was changed by o1. [211]
<br>o3<br>
<br>On December 20, 2024, OpenAI unveiled o3, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11862161) the follower of the o1 thinking model. OpenAI likewise unveiled o3-mini, a lighter and faster variation of OpenAI o3. Since December 21, 2024, this model is not available for . According to OpenAI, they are checking o3 and o3-mini. [212] [213] Until January 10, 2025, security and security scientists had the opportunity to obtain early access to these designs. [214] The model is called o3 instead of o2 to prevent confusion with telecoms services service provider O2. [215]
<br>Deep research<br>
<br>Deep research study is a representative established by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to carry out extensive web browsing, information analysis, and synthesis, [delivering detailed](https://uedf.org) reports within a timeframe of 5 to thirty minutes. [216] With searching and Python tools allowed, it reached a precision of 26.6 percent on HLE (Humanity's Last Exam) benchmark. [120]
<br>Image classification<br>
<br>CLIP<br>
<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to examine the semantic resemblance in between text and images. It can notably be used for image classification. [217]
<br>Text-to-image<br>
<br>DALL-E<br>
<br>Revealed in 2021, DALL-E is a [Transformer model](https://easy-career.com) that develops images from textual descriptions. [218] DALL-E utilizes a 12-billion-parameter version of GPT-3 to analyze natural language inputs (such as "a green leather bag shaped like a pentagon" or "an isometric view of a sad capybara") and create [matching images](https://git.epochteca.com). It can create images of sensible things ("a stained-glass window with a picture of a blue strawberry") along with things that do not exist in reality ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.<br>
<br>DALL-E 2<br>
<br>In April 2022, OpenAI revealed DALL-E 2, an upgraded version of the design with more realistic outcomes. [219] In December 2022, OpenAI released on GitHub software application for Point-E, a brand-new basic system for converting a text description into a 3-dimensional model. [220]
<br>DALL-E 3<br>
<br>In September 2023, OpenAI revealed DALL-E 3, a more effective model better able to generate images from complex descriptions without manual timely engineering and render complex details like hands and text. [221] It was released to the general public as a ChatGPT Plus function in October. [222]
<br>Text-to-video<br>
<br>Sora<br>
<br>Sora is a text-to-video design that can produce videos based upon short detailed prompts [223] in addition to extend existing videos forwards or backwards in time. [224] It can generate videos with resolution approximately 1920x1080 or 1080x1920. The maximal length of generated videos is unidentified.<br>
<br>Sora's advancement group called it after the Japanese word for "sky", to represent its "endless imaginative capacity". [223] Sora's technology is an adaptation of the technology behind the [DALL ·](https://www.contraband.ch) E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos in addition to copyrighted videos certified for that purpose, but did not expose the number or the precise sources of the videos. [223]
<br>OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, [stating](http://114.132.230.24180) that it could create videos up to one minute long. It likewise shared a technical report highlighting the techniques utilized to train the model, and the design's capabilities. [225] It acknowledged a few of its drawbacks, [consisting](https://hebrewconnect.tv) of battles simulating intricate physics. [226] Will Douglas Heaven of the MIT Technology Review called the demonstration videos "impressive", however kept in mind that they must have been cherry-picked and might not represent Sora's common output. [225]
<br>Despite uncertainty from some scholastic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have revealed substantial interest in the technology's capacity. In an interview, actor/filmmaker Tyler Perry revealed his astonishment at the technology's capability to generate practical video from text descriptions, citing its possible to revolutionize storytelling and material creation. He said that his excitement about Sora's possibilities was so strong that he had decided to stop briefly strategies for expanding his Atlanta-based motion picture studio. [227]
<br>Speech-to-text<br>
<br>Whisper<br>
<br>Released in 2022, Whisper is a general-purpose speech acknowledgment model. [228] It is trained on a large dataset of varied audio and is also a multi-task model that can carry out [multilingual speech](https://skillfilltalent.com) recognition along with speech translation and language identification. [229]
<br>Music generation<br>
<br>MuseNet<br>
<br>Released in 2019, MuseNet is a deep neural net trained to anticipate subsequent musical notes in MIDI [music files](https://gitlab.companywe.co.kr). It can create songs with 10 instruments in 15 styles. According to The Verge, a song produced by MuseNet tends to start fairly but then fall under chaos the longer it plays. [230] [231] In pop culture, preliminary applications of this tool were used as early as 2020 for the web mental thriller Ben Drowned to produce music for the titular character. [232] [233]
<br>Jukebox<br>
<br>Released in 2020, Jukebox is an [open-sourced algorithm](http://www.vmeste-so-vsemi.ru) to create music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a snippet of lyrics and outputs song samples. OpenAI specified the tunes "show local musical coherence [and] follow traditional chord patterns" but acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that duplicate" and that "there is a significant gap" between Jukebox and human-generated music. The Verge specified "It's technically outstanding, even if the outcomes seem like mushy variations of tunes that might feel familiar", while Business Insider specified "remarkably, some of the resulting tunes are appealing and sound genuine". [234] [235] [236]
<br>Interface<br>
<br>Debate Game<br>
<br>In 2018, OpenAI released the Debate Game, which teaches machines to discuss toy issues in front of a human judge. The purpose is to research whether such a technique may help in auditing [AI](https://heartbeatdigital.cn) decisions and in establishing explainable [AI](https://digital-field.cn:50443). [237] [238]
<br>Microscope<br>
<br>Released in 2020, Microscope [239] is a collection of visualizations of every considerable layer and nerve cell of 8 neural network models which are frequently studied in interpretability. [240] Microscope was developed to analyze the functions that form inside these neural networks easily. The designs consisted of are AlexNet, VGG-19, various [variations](https://repo.serlink.es) of Inception, and [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:HunterY514213) various versions of [CLIP Resnet](https://app.zamow-kontener.pl). [241]
<br>ChatGPT<br>
<br>Launched in November 2022, ChatGPT is an expert system tool built on top of GPT-3 that provides a conversational interface that allows users to ask questions in natural language. The system then reacts with a response within seconds.<br>